Browsing by Author "Xin, Wuping"

Now showing 1 - 5 of 5
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    Development of Real-Time Traffic Adaptive Crash Reduction Measures for the Westbound I-94/35W Commons Section
    (University of Minnesota Center for Transportation Studies, 2008-12) Hourdos, John; Xin, Wuping; Michalopoulos, Panos
    Much research has been conducted in the development, implementation, and evaluation of innovative ITS technologies aiming to improve traffic operations and driving safety. An earlier project succeeded in supporting the hypothesis that certain traffic conditions are favorable to crashes and in developing real-time algorithms for the estimation of crash probability from detector measurements. Following this accomplishment a natural question is “how can this help prevent crashes?” This project has the ambitious plan of not only answering this question but also providing a multifaceted approach that can offer different types of solutions to an agency aimed at reducing crashes in this and other similar locations. This project has two major objectives; first it aimed at utilizing a cutting edge 3D virtual reality system to design and visualize different driver warning systems specifically for the I-94 westbound high crash location in Minneapolis, MN. Second, in view of the desire of local engineers for a more traditional approach, this project explored the use of existing micro-simulation models in the evaluation of safety improvements for the aforementioned high crash area. This report describes the results of these investigations but more importantly describes the lessons learned in the process of the research. These lessons are important because they highlight gaps of technology and knowledge that hampered this and other research projects with similar objectives.
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    Enhanced Micro-Simulation Models for Accurate Safety Assessment of Traffic Management ITS Solutions
    (University of Minnesota Center for Transportation Studies, 2008-11) Xin, Wuping; Hourdos, John; Michalopoulos, Panos
    Much research has been conducted in the development, implementation, and evaluation of innovative ITS technologies aiming to improve traffic operations and driving safety. Existing micro-simulation modeling only describes normative car-following behaviors devoid of weakness and risks associated with real-life everyday driving. This research aims to develop a new behavioral car-following model that is pertinent to the true nature of everyday human driving. Unlike traditional car-following models that deliberately prohibit vehicle collisions, this new model builds upon multi-disciplinary findings explicitly taking into account perceptual thresholds, judgment errors, anisotropy of reaction times and driver inattention, in order to replicate “less-than-perfect” driving behavior with all its weakness and risks. Most importantly, all parameters of this model have direct physical meaning; this ensures vehicle collisions are replicated as a result of behavioral patterns rather than simply being numerical artifacts of the model. Meanwhile, vehicle trajectories were extracted from real-life crashes collected from a freeway section of I-94WB This is by far the first data collection efforts that aim to collect vehicle trajectories from real-life crashes to aid car-following modeling. These data were employed in this study to test, calibrate and validate the model. This new model is successful in replicating these vehicle trajectories as well as crashes.
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    Evaluation and Improvement of the Stratified Ramp Metering Algorithm Through Microscopic Simulation - Phase II
    (2005-12-01) Michalopoulos, Panos; Xin, Wuping; Hourdos, John
    A new ramp metering strategy implemented on the Twin Cities freeway system to reduce ramp waiting times was evaluated through microsimulation of freeway activity. The study compared Stratified Ramp Metering strategy with the previous Zone Metering Strategy and with no control strategy. Comparison with Zone, which was designed to favor freeway flow, showed the new strategy succeeded in greatly reducing ramp delays and lines. When compared to the results of no control strategy, it reduces freeway travel time, increases freeway speed, smoothes the flow of traffic, and reduces the number of stops. However, travel time, fuel consumption and pollutant emissions are unpredictable under the newer system. Compared to no control strategy, such measures of effectiveness may improve or worsen depending on the freeway patterns and demand. Based on these findings, the researchers will seek improvements to the design of the Stratified Ramp Metering algorithm so as to factor in disruptive traffic patterns.
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    Stochastic congestion and pricing model with endogenous departure time selection and heterogeneous travelers
    (2015) Xin, Wuping; Levinson, David M
    This paper proposes a stochastic congestion and pricing model that combines a bottleneck model with stochastic queuing to study roadway congestion and pricing. Employing this model, two pricing schemes are developed: one is omniscient pricing for which the transportation administrative agency is assumed to be aware of each and every traveler's cost structure (i.e., their detailed valuation of journey cost as well as early and late penalties), and the other is observable pricing, for which only queuing delay is considered. Travelers are characterized by their late-acceptance level and the effects of various compositions of late-averse, late-tolerant and late-neutral travelers on congestion patterns with and without pricing are discussed. Numerical simulation indicates that omniscient pricing scheme is most effective in suppressing peak hour congestion and distributing demands over longer time horizon. Also, congestion pricing is found to be more effective when travelers have diversified cost structures than identical cost structures, and congestion is better reduced with heterogeneous traveler composition than with single composition. This is consistent with earlier studies in the literature. In addition, the simulation results indicate that omniscient pricing in general reduces Expected Total Social Cost<(with or without the return of the congestion fee). However, the ultimate benefits of a certain pricing scheme depend on travelers' cost structure as well as the composition of late-tolerant, late-averse and late-neutral travelers in the entire population; extreme situations such as 100% late-averse or 100% late-tolerant traveler composition deserves extra attention when analyzing different pricing schemes.
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    Streamlining of the Traffic Modeling Process for Implementation in the Twin Cities Freeway Network - Phase II
    (2006-05-01) Xin, Wuping; Hourdos, John; Michalopoulos, Panos
    Comprehensive methodologies are proposed for improving the quality of both freeway and arterial intersections traffic volumes for the purpose of enabling and improving traffic simulations. Specifically, established and enhanced procedures for checking and correcting freeway temporal errors are integrated with an optimization-based algorithm for reconciling spatial inconsistencies in freeway traffic counts. In addition to this, an empirical methodology is further integrated to balance arterial intersection traffic counts. The proposed methodologies have been successfully automated and implemented as two computer programs, i.e., TradaX for processing freeway volume and ArtBaT for arterial intersection traffic counts. Initial evaluations of these tools suggest that they have the potential of reducing total modeling time by 25% ~ 30%, while resulting in improved calibration of simulation models, more reliable analysis, and better use of staff resources for meeting project deadlines.